Morgan Stanley: Stock Price, Wealth Management, and Core Business Explained

For the better part of three years, the market has been singing a one-note ballad. That note, of course, was Artificial Intelligence, and it was loud enough to drown out everything else. It was the theme that powered portfolios from Main Street to Wall Street, turning the stock market into a seemingly can’t-miss proposition. But music, especially when it’s played that loudly for that long, eventually has to end. Or, at the very least, it has to change.

According to a new research note, Morgan Stanley warns AI stock boom is running out of steam, and the data suggests we’ve reached an inflection point. And while the headlines might scream about the end of the AI boom, the data presents a far more nuanced, and frankly, more interesting picture. The core discrepancy is this: The S&P 500 RavenPack AI Sentiment Index, a basket of stocks at the heart of the revolution, is up a mere 6% this year. The broader S&P 500, meanwhile, is clipping along at 14.2%.

That’s not just a minor deviation; it’s a statistical flare sent up from the engine room of the market. It signals that the narrative is no longer perfectly aligned with the numbers. And when that happens, it’s time to pay very close attention.

The Anatomy of a Concentrated Rally

To understand where we might be going, we first have to appreciate the sheer scale of what’s happened. According to the team at `Morgan Stanley Wealth Management`, since the public debut of ChatGPT in November 2022, the AI data center ecosystem has been the market's prime mover. These stocks have accounted for roughly 75% of S&P 500 returns, 80% of its earnings growth, and a staggering 90% of its capital expenditures growth. The S&P 500 itself has gained about 90%—to be more exact, a robust 90% in that period.

This isn't a rally; it's a dependency. It’s the financial equivalent of a blockbuster movie franchise propping up an entire studio’s annual revenue. As long as the superhero sequels keep landing, everything looks fantastic. But what happens when the audience starts to get tired of the same story?

Lisa Shalett, the CIO at Morgan Stanley Wealth Management, put it bluntly, stating "we believe we’re closer to the seventh inning than the first." This is analyst-speak for "the easy money has been made." The initial, explosive phase of a boom is characterized by indiscriminate buying and a belief in a limitless future. The later innings are defined by skepticism, a focus on fundamentals, and a much, much narrower path to victory.

Why the shift in sentiment? I’ve looked at hundreds of these market reports, and the reasoning here is unusually direct. It’s not about vague macroeconomic fears; it’s about tangible stress points appearing in the system.

The Gravity of Negative Cash Flow

Morgan Stanley’s report identifies several factors, but one stands out with clinical brutality: AI hyperscaler free-cash-flow growth "has turned negative."

Let’s be perfectly clear. Free cash flow is the oxygen for a company, especially one in a capital-intensive growth phase. It’s the money left over after paying for everything required to run and expand the business. When the very companies funding this AI arms race—the giants building the data centers and buying the chips—see their own cash generation go into reverse, the entire ecosystem feels the pressure. It’s a fundamental constraint that no amount of marketing hype can overcome.

This is the part of the report I find genuinely telling. For years, the narrative has been that spending on AI was a blank-check item. Now, the checkbook is being audited.

The other symptoms are just as concerning. The report points to accelerating price competition and deal-making that "smacks of speculation and vendor-financing strategies of old." That last point is particularly revealing. Vendor financing (a classic late-cycle sign where sellers fund the buyers just to book a sale) is what companies resort to when organic demand starts to dry up. It’s a way to keep the music playing, but it’s an artificial and unsustainable one.

So, is the party over? Or is it just moving to a different room? Maja Vujinovic, CEO of Digital Assets FG Nexus, argues it’s the latter—a “shift in gears” from a sprint to a marathon. The argument is that the initial land grab for chips and data centers is evolving into a more measured phase focused on efficiency and return on investment. This makes logical sense. The first wave was about building the infrastructure; the next must be about proving it can generate profit.

But this "shift" is precisely where the danger lies for the average investor, perhaps one managing their portfolio on a platform like `Etrade Morgan Stanley` or Schwab. The rising tide that lifted every boat with "AI" in its pitch deck is receding. Now, we're about to find out which companies actually have a working engine and which were just floating on the hype. How do we, as analysts, differentiate between a genuine strategic pivot to profitability and a company simply rebranding a slowdown because the easy capital has run out?

The Market's Inevitable Recalibration

The AI boom isn't over. Let's not be hyperbolic. But the first phase of the AI boom—the one fueled by pure narrative, cheap capital, and the suspension of disbelief—is unequivocally finished.

For the past three years, the market has rewarded vision. Now, it’s demanding results. The core question has shifted from "What could you build?" to "What have you earned?" The advice from Morgan Stanley to rotate into "real assets" like commodities and energy infrastructure isn't just a defensive crouch; it's a rational response to a market that is finally waking up from a very expensive dream.

The game of buying a ticker symbol because it was mentioned in the same breath as "generative AI" is over. The era of blind faith has been replaced by the era of the spreadsheet. The party isn't over, but the lights are on, and the market is finally asking everyone to pay their tab.